Selection of optimal wavelengths for optical soiling modelling and detection in photovoltaic modules

TL;DR

This study demonstrates that using a few monochromatic measurements to extract spectral transmittance profiles significantly enhances the detection and quantification of soiling losses in photovoltaic modules across various materials and conditions.

Contribution

It introduces a method to improve soiling detection accuracy by selecting optimal wavelengths for spectral measurements, outperforming single-wavelength sensors.

Findings

Spectral transmittance profiles improve soiling detection accuracy.

Optimal wavelength selection reduces measurement errors.

Method is robust across different PV materials and conditions.

Abstract

Soiling impacts the photovoltaic (PV) module performance by reducing the amount of light reaching the photovoltaic cells and by changing their external spectral response. Currently, the soiling monitoring market is moving toward optical sensors that measure transmittance or reflectance, rather than directly measuring the impact of soiling on the performance of photovoltaic modules. These sensors, which use a single optical measurement, are not able to correct the soiling losses that depend on the solar irradiance spectra and on the spectral response of the monitored PV material. This work investigates methods that can improve the optical detection of soiling by extracting the full soiling spectrum profiles using only two or three monochromatic measurements. Spectral transmittance data, measured with a spectrophotometer and collected during a 46-week experimental soiling study carried out in Ja\'en, Spain, was analysed in this work. The use of a spectral profile for the hemispherical transmittance of soiled PV glass is found to significantly improve the soiling detection, returning the lowest errors independently of the PV materials and irradiance conditions. In addition, this work shows that it is also possible to select the measurement wavelengths to minimize the soiling loss detection error depending on the monitored PV semiconductor material (silicon, CdTe, a-Si, CIGS and a representative perovskite). The approaches discussed in this work are also found to be more robust to potential measurement errors compared to single wavelength measurement techniques.